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StreaMD: the toolkit for high-throughput molecular dynamics simulations
A. Ivanova, O. Mokshyna, P. Polishchuk
Status not-indexed Language English Country England, Great Britain
Document type Journal Article
Grant support
LUAUS23262
Ministerstvo Školství, Mládeže a Tělovýchovy
LM2018131
Ministerstvo Školství, Mládeže a Tělovýchovy
LUAUS23262
Ministerstvo Školství, Mládeže a Tělovýchovy
CZ.02.1.01/0.0/0.0/16_019/0000868
European Regional Development Fund
NLK
BioMedCentral
from 2009-12-01
BioMedCentral Open Access
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Directory of Open Access Journals
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Free Medical Journals
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PubMed Central
from 2009
Europe PubMed Central
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ProQuest Central
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Open Access Digital Library
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Open Access Digital Library
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Health & Medicine (ProQuest)
from 2009-01-01
ROAD: Directory of Open Access Scholarly Resources
from 2009
Springer Journals Complete - Open Access
from 2009-01-12
Springer Nature OA/Free Journals
from 2009-01-12
Springer Nature OA/Free Journals
from 2009-12-01
- Publication type
- Journal Article MeSH
Molecular dynamics simulations serve as a prevalent approach for investigating the dynamic behaviour of proteins and protein-ligand complexes. Due to its versatility and speed, GROMACS stands out as a commonly utilized software platform for executing molecular dynamics simulations. However, its effective utilization requires substantial expertise in configuring, executing, and interpreting molecular dynamics trajectories. Existing automation tools are constrained in their capability to conduct simulations for large sets of compounds with minimal user intervention, or in their ability to distribute simulations across multiple servers. To address these challenges, we developed a Python-based tool that streamlines all phases of molecular dynamics simulations, encompassing preparation, execution, and analysis. This tool minimizes the required knowledge for users engaging in molecular dynamics simulations and can efficiently operate across multiple servers within a network or a cluster. Notably, the tool not only automates trajectory simulation but also facilitates the computation of free binding energies for protein-ligand complexes and generates interaction fingerprints across the trajectory. Our study demonstrated the applicability of this tool on several benchmark datasets. Additionally, we provided recommendations for end-users to effectively utilize the tool.Scientific contributionThe developed tool, StreaMD, is applicable to different systems (proteins, ligands and their complexes including co-factors) and requires a little user knowledge to setup and run molecular dynamics simulations. Other features of StreaMD are seamless integration with calculation of MM-GBSA/PBSA binding free energies and protein-ligand interaction fingerprints, and running of simulations within distributed environments. All these will facilitate routine and massive molecular dynamics simulations.
References provided by Crossref.org
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- $a Molecular dynamics simulations serve as a prevalent approach for investigating the dynamic behaviour of proteins and protein-ligand complexes. Due to its versatility and speed, GROMACS stands out as a commonly utilized software platform for executing molecular dynamics simulations. However, its effective utilization requires substantial expertise in configuring, executing, and interpreting molecular dynamics trajectories. Existing automation tools are constrained in their capability to conduct simulations for large sets of compounds with minimal user intervention, or in their ability to distribute simulations across multiple servers. To address these challenges, we developed a Python-based tool that streamlines all phases of molecular dynamics simulations, encompassing preparation, execution, and analysis. This tool minimizes the required knowledge for users engaging in molecular dynamics simulations and can efficiently operate across multiple servers within a network or a cluster. Notably, the tool not only automates trajectory simulation but also facilitates the computation of free binding energies for protein-ligand complexes and generates interaction fingerprints across the trajectory. Our study demonstrated the applicability of this tool on several benchmark datasets. Additionally, we provided recommendations for end-users to effectively utilize the tool.Scientific contributionThe developed tool, StreaMD, is applicable to different systems (proteins, ligands and their complexes including co-factors) and requires a little user knowledge to setup and run molecular dynamics simulations. Other features of StreaMD are seamless integration with calculation of MM-GBSA/PBSA binding free energies and protein-ligand interaction fingerprints, and running of simulations within distributed environments. All these will facilitate routine and massive molecular dynamics simulations.
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